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import gradio as gr
import requests
# Define the function to call the model hosted on Hugging Face
def get_fertilizer_recommendation(crop_name, target_yield, field_size, ph_water, organic_carbon, total_nitrogen, phosphorus, potassium, soil_moisture):
# Replace this with the URL of your Hugging Face model
url = "https://api-inference.huggingface.co/models/your-model-name"
headers = {"Authorization": "Bearer YOUR_HUGGING_FACE_API_KEY"}
# Define the input payload
payload = {
'Crop Name': [crop_name],
'Target Yield': [target_yield],
'Field Size': [field_size],
'pH (water)': [ph_water],
'Organic Carbon': [organic_carbon],
'Total Nitrogen': [total_nitrogen],
'Phosphorus (M3)': [phosphorus],
'Potassium (exch.)': [potassium],
'Soil moisture': [soil_moisture]
}
# Make the request to the model
response = requests.post(url, headers=headers, json=payload)
result = response.json()
# Extract the relevant output fields
output = f"""
Predicted Fertilizer Requirements:
Nitrogen (N) Need: {result['Nitrogen (N) Need']}
Phosphorus (P2O5) Need: {result['Phosphorus (P2O5) Need']}
Potassium (K2O) Need: {result['Potassium (K2O) Need']}
Organic Matter Need: {result['Organic Matter Need']}
Lime Need: {result['Lime Need']}
Lime Application - Requirement: {result['Lime Application - Requirement']}
Organic Matter Application - Requirement: {result['Organic Matter Application - Requirement']}
1st Application - Requirement (1): {result['1st Application - Requirement (1)']}
1st Application - Requirement (2): {result['1st Application - Requirement (2)']}
Lime Application - Instruction: {result['Lime Application - Instruction']}
Lime Application: {result['Lime Application']}
Organic Matter Application - Instruction: {result['Organic Matter Application - Instruction']}
Organic Matter Application: {result['Organic Matter Application']}
1st Application: {result['1st Application']}
1st Application - Type fertilizer (1): {result['1st Application - Type fertilizer (1)']}
1st Application - Type fertilizer (2): {result['1st Application - Type fertilizer (2)']}
"""
return output
# Create the Gradio interface
interface = gr.Interface(
fn=get_fertilizer_recommendation,
inputs=[
gr.inputs.Textbox(label="Crop Name"),
gr.inputs.Number(label="Target Yield"),
gr.inputs.Number(label="Field Size"),
gr.inputs.Number(label="pH (water)"),
gr.inputs.Number(label="Organic Carbon"),
gr.inputs.Number(label="Total Nitrogen"),
gr.inputs.Number(label="Phosphorus (M3)"),
gr.inputs.Number(label="Potassium (exch.)"),
gr.inputs.Number(label="Soil moisture"),
],
outputs="text",
title="Fertilizer Application Advisor",
description="Input the details of your field and get fertilizer recommendations."
)
# Launch the interface
interface.launch()
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